Applied AI Scientist

This is a fully remote position, open to applicants in California, +2 more states.

📋 Description

• Design, develop, and deploy AI-driven applications that convert extensive geospatial data into actionable insights and predictive intelligence.

• Construct and manage comprehensive AI/ML pipelines encompassing data ingestion, preprocessing, feature engineering, training, evaluation, and production inference.

• Implement reasoning models, vision-language models, and multimodal AI systems that integrate imagery, geospatial signals, and structured data into production.

• Architect enterprise-level training and experimentation frameworks utilizing automated pipelines, experiment tracking, benchmarking, and reproducible evaluation.

• Generate synthetic datasets and testing frameworks to assess model performance, robustness, and behavior in edge cases.

• Collaborate with domain experts, software engineers, product managers, and research partners to transform Earth intelligence challenges into practical AI solutions.

• Enhance models and inference systems for scalability, latency, cost-effectiveness, and reliability on contemporary cloud infrastructure.

• Implement and sustain production inference systems, including monitoring, model versioning, retraining workflows, and performance tracking.

• Stay updated with foundation models, generative AI, multimodal learning, and reasoning systems, translating research advancements into applicable systems.

• Uphold engineering standards through code reviews, documentation, experimentation discipline, and collaborative problem-solving.

• Contribute to the development of next-generation Earth AI capabilities through partnerships with research organizations and technology collaborators.

⛳️ Requirements

• MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or a related technical field, or equivalent practical experience.

• Over 5 years of experience in building and deploying machine learning systems within production environments.

• Proven experience in designing and delivering end-to-end ML pipelines, including data processing, training automation, evaluation frameworks, and scalable inference.

• Practical experience in developing and deploying deep learning models in vision-language models, multimodal learning, reasoning models, large language models, computer vision, or geospatial AI.

• Strong programming proficiency in Python.

• Familiarity with PyTorch, TensorFlow, or JAX.

• Experience in constructing reproducible experimentation pipelines, which include model evaluation, dataset versioning, and experiment tracking.

• Experience in deploying models in production settings using modern cloud infrastructure and containerized systems.

• Knowledge of distributed training, large-scale data processing, and model optimization techniques.

• Ability to work collaboratively across research, engineering, and product teams.

• U.S. Person status required: U.S. citizen, permanent resident, Asylee, or Refugee.

• Certain roles may be subject to U.S. export control laws requiring U.S. Person status.

• Preferred: experience with geospatial data, remote sensing, satellite imagery, or Earth observation systems.

• Preferred: experience in building or fine-tuning foundation models, multimodal models, or agentic AI systems.

• Preferred: familiarity with Google Cloud Platform (GCP).

• Preferred: experience in implementing model monitoring, evaluation pipelines, and automated retraining systems.

• Preferred: contributions to open-source AI projects, research publications, or patents.

🏝️ Benefits

• Competitive total rewards package.

• Robust 401(k) with company match.

• Mental health resources.

• Student loan repayment assistance.

• Adoption reimbursement.

• Pet insurance.

• Incentive eligible, with a target based on contribution, company performance, and/or individual results.